The Age of Information is truly here. Every day, people add 2.5 quintillion bytes of new data to the Internet, doubling the amount of global data every two years.
Companies are able to gather massive amounts of information about their customers and operations from this data, collectively called big data. They then use business intelligence to uncover ways to increase revenue, improve the accuracy of decisions, save costs, and generate innovative ideas.
Here are just a few examples of how companies are putting big data to work:
- Target analyzes past purchases to figure out what products customers are most likely to buy in the future. Leveraging this data, it distributes coupons that align with the future product predictions.
- New York City uses data to identify buildings most at risk of deadly fires and sends inspectors to those properties more frequently.
- Google and the Center for Disease Control are able to track flu outbreaks as they occur.
- Disney World’s MyMagic+ wristbands help Disney understand how visitors interact with the park and give characters the “magical” ability to greet children by name.
Despite its promise, however, many organizations struggle to leverage data effectively. Just 23% of executives at large organizations believe their big data initiatives are successful – and only 52% consider their initiatives “somewhat successful.”
At Capella University, students pursuing an MBA in Business Intelligence learn three ways big data pays off.
1. Set a Business Intelligence Strategy.
Companies struggle with business intelligence when they don’t have a clear plan for how they will use the data gathered. The McKinsey Quarterly reports that when companies strategically use big data and analytics, they experience profit and productivity gains 5-6% higher than companies that don’t. But most companies only analyze 12% of the data they collect – leaving most of their business intelligence potential on the table.
Students prepare to run successful big data initiatives in their future career by learning how to:
- Develop a business intelligence strategy that aligns with the organization’s goals.
- Choose the best statistical methods, modeling tools, and data collection/reporting techniques.
- Ensure that the organization has the teams and resources in place to execute a business intelligence initiative.
2. Communicate Clearly.
The biggest challenges organizations face in using business intelligence effectively are often related to communication. Only 48% of business and IT leaders understand the full potential of big data, leaving business intelligence initiatives without the funding, resources, and follow-through they need to succeed.
The 2013 IBM Institute for Business Value research study also found that a low level of trust between executives and IT professionals leads to redundancy and low confidence in results.
Developing communications skills is critical and coursework emphasizes the following:
- Obtaining executive buy-in so that business intelligence projects receive internal support.
- Nurturing interactions between executives and IT teams so that everyone is on the same page regarding outcomes, milestones, deliverables, time, and budget.
- Define initiatives in terms of business questions they will answer versus the data collection tactics they will use.
3. Get Value from the Data.
When leading a business intelligence initiative, it’s easy to get caught up in collecting data. But what ultimately matters isn’t the amount of data collected, it’s what organizations get out of it. Ideally, organizations will use their business intelligence initiatives to uncover new insights about their target market, solve internal problems, and improve operations.
Specialization courses teach students skills needed to drive value, including:
- Making evidence-based business decisions based on quantitative and qualitative data.
- Cutting down silos between parts of your organization so multiple business units can benefit from the data.
- Leading innovation to solve challenges uncovered during business intelligence operations.
Big data professionals are also well educated, with 86% holding at least a master’s degree. If you’re interested in expanding your knowledge and advancing your career in the growing field of big data, learn more about Capella’s MBA in Business Intelligence program.